Machine learning models for dementia screening to classify brain amyloid positivity on positron emission tomography using blood markers and demographic characteristics: a retrospective observational study

Machine learning models for dementia screening to classify brain amyloid positivity on positron emission tomography using blood markers and demographic characteristics: a retrospective observational study

Abstract Background Intracerebral amyloid β (Aβ) accumulation is considered the initial observable event in the pathological process of Alzheimer’s disease (AD). Efficient screening for amyloid pathology is critical for identifying patients for early treatment. This study developed machine learning...

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Bibliographic Details
Main Authors: Noriyuki Kimura, Kotaro Sasaki, Teruaki Masuda, Takuya Ataka, Mariko Matsumoto, Mika Kitamura, Yosuke Nakamura, Etsuro Matsubara
Format: Article
Language:English
Published: BMC 2025-01-01
Series:Alzheimer’s Research & Therapy
Subjects:
AD
Alzheimer’s disease
Amyloid β positivity
Dementia
Machine learning
Online Access:https://doi.org/10.1186/s13195-024-01650-1
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https://doi.org/10.1186/s13195-024-01650-1

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